LAUSR

Mental health problems have always existed in human life. However, factors such as lifestyle changes and industrialization affect modern human mental health. A common mental illness is depressive disorder, and a large number of patients are not even aware they have it. Due to the harmful influences of depressive disorder on quality of life, timely and accurate diagnosis is a matter of extreme prominence. The aim of this study is to design a web-based expert system for diagnosing depression using the fuzzy Delphi method by estimating the weights and importance of depression symptoms. Fuzzy Logic is adopted to calculate the level of depression. Two thresholds are obtained, namely lack of depression and severe depression. Finally, the level of depression for each person is estimated by virtue of the calculated value’s proximity to these two opposing points. Java Expert System Shell is used to build the knowledge base. Sensitivity and specificity analysis are performed with 238 participants. The proposed system appears helpful for everyone, from ordinary persons to specialists in medical environments. It can also be useful to train psychology students in the area of diagnostic reasoning.